In order to solve the inconsistency of device spectral gamut which happens in cross-media spectral color reproduction process, a new spectral gamut mapping model is established in visual features weighted principal component analysity (PCA) space. The standard colorimetric observer matching function is used to construct weight coefficient, which is employed to weight high dimensional spectra. Then the first three components of weighted spectra are extracted by using the PCA method, so that the low dimensional visual features weighted PCA space is set up. In the weighted PCA space, the segment maxima gamut bounduny descriptor algorithm adopted to describe the device spectral gamut, and the outside spectrum is mapped into the device spectral gamut by clipping method. The experimental result indicates that the new model can realize more visual matching than the commonly used method in PCA space, and solve the inconsistency of device spectral gamut more effectively.